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Shen C, Zheng B, Chen Z, Zhang W, Chen X, Xu S, Ji J, Fang X, Shi C. Identification of prognostic models for glycosylation-related subtypes and tumor microenvironment infiltration characteristics in clear cell renal cell cancer. Heliyon 2024; 10:e27710. [PMID: 38515689 PMCID: PMC10955297 DOI: 10.1016/j.heliyon.2024.e27710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 03/23/2024] Open
Abstract
Background One of the most fatal forms of cancer of the urinary system, renal cell carcinoma (RCC), significantly negatively impacts human health. Recent research reveals that abnormal glycosylation contributes to the growth and spread of tumors. However, there is no information on the function of genes related to glycosylation in RCC. Methods In this study, we created a technique that can be used to guide the choice of immunotherapy and chemotherapy regimens for RCC patients while predicting their survival prognosis. The Cancer Genome Atlas (TCGA) provided us with patient information, while the GeneCards database allowed us to collect genes involved in glycosylation. GSE29609 was used as external validation to assess the accuracy of prognostic models. The "ConsensusClusterPlus" program created molecular subtypes based on genes relevant to glycosylation discovered using differential expression analysis and univariate Cox analysis. We examined immune cell infiltration as measured by estimate, CIBERSORT, TIMER, and ssGSEA algorithms, Tumor Immune Dysfunction and Exclusion (TIDE) and exclusion of tumour stemness indices (TSIs) based on glycosylation-related molecular subtypes and risk profiles. Stratification, somatic mutation, nomogram creation, and chemotherapy response prediction were carried out based on risk factors. Results We built and verified 16 gene signatures associated with the prognosis of ccRCC patients, which are independent prognostic variables, and identified glycosylation-related genes by bioinformatics research. Cluster 2 is associated with lower human leukocyte antigen expression, worse overall survival, higher immunological checkpoints, and higher immune escape scores. In addition, cluster 2 had significantly better angiogenic activity, mesenchymal EMT, and stem ability scores. Higher immune checkpoint genes and human leukocyte antigens are associated with lower overall survival and a higher risk score. Higher estimated and immune scores, lesser tumor purity, lower mesenchymal EMT, and higher stem scores were all characteristics of the high-risk group. High amounts of tumor-infiltrating lymphocytes, a high mutation load, and a high copy number alteration frequency were present in the high-risk group.Discussion.According to our research, the 16-gene prognostic signature may be helpful in predicting prognosis and developing individualized treatments for patients with renal clear cell carcinoma, which may result in new personalized management options for these patients.
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Affiliation(s)
- Cheng Shen
- Department of Urology, Affiliated Hospital 2 of Nantong University, China
- Medical Research Center, Affiliated Hospital 2 of Nantong University, China
| | - Bing Zheng
- Department of Urology, Affiliated Hospital 2 of Nantong University, China
| | - Zhan Chen
- Department of Urology, Affiliated Hospital 2 of Nantong University, China
- Medical Research Center, Affiliated Hospital 2 of Nantong University, China
| | - Wei Zhang
- Department of Urology, Affiliated Hospital 2 of Nantong University, China
| | - Xinfeng Chen
- Department of Urology, Affiliated Hospital 2 of Nantong University, China
| | - Siyang Xu
- Clinical Medicine Specialty, Xinglin College of Nantong University, China
| | - Jianfeng Ji
- Department of Burn and plastic surgery, Affiliated Hospital 2 of Nantong University, China
| | - Xingxing Fang
- Nephrology Department, Affiliated Hospital 2 of Nantong University, China
| | - Chunmei Shi
- Department of Urology, Affiliated Hospital 2 of Nantong University, China
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Wu LL, Yuan SF, Lin QY, Chen GM, Zhang W, Zheng WE, Lin HL. Construction and validation of risk model of EMT-related prognostic genes for kidney renal clear cell carcinoma. J Gene Med 2023; 25:e3549. [PMID: 37271571 DOI: 10.1002/jgm.3549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/03/2023] [Accepted: 05/18/2023] [Indexed: 06/06/2023] Open
Abstract
BACKGROUND Kidney renal clear cell carcinoma (KIRC) is a prevalent type of urological malignancy. The present study aimed to predict biomarkers for KIRC. METHODS We collected transcriptomic and clinical information for KIRC from The Cancer Genome Atlas and GSE22541 cohorts. RESULTS Unsupervised clustering of 35 epithelial-mesenchymal transformation (EMT)-related differentially expressed gene profiles divided samples into two clusters with distinct immune characteristics. Six genes (IL20RB, DDC, ANKRD36BP2, F2RL1, TEK, and AMN) were found to construct a prognostic risk model using multivariate Cox regression analysis. Kaplan-Meier analysis suggested the better prognosis of the KIRC patients in the low-risk group than that in the high-risk group. Immune infiltration analyses was conducted using xCell and single-sample gene set enrichment analysis, indicating that the risk score was associated with the immune microenvironment of the KIRC. Prognostic marker gene-targeted medications with high drug sensitivity were predicted in KIRC patients. CONCLUSIONS In summary, the present study identified IL20RB, DDC, ANKRD36BP2, F2RL1, TEK, and AMN as prognostic biomarkers, providing insight into immunotherapy and gene-targeted drugs of KIRC.
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Affiliation(s)
- Li Li Wu
- Department of Medical Oncology, Rui'an People's Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shao-Fei Yuan
- Department of Medical Oncology, Rui'an People's Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Qiu-Yan Lin
- Department of Medical Oncology, Rui'an People's Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Guang-Ming Chen
- Department of Urology, Rui'an People's Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Wu Zhang
- Department of Medical Oncology, Rui'an People's Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Wei-E Zheng
- Department of Chemoradiation and Oncology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Hua Long Lin
- Department of Medical Oncology, Rui'an People's Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Wu X, Li F, Xie W, Gong B, Fu B, Chen W, Zhou L, Luo L. A novel oxidative stress-related genes signature associated with clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma. Front Oncol 2023; 13:1184841. [PMID: 37601683 PMCID: PMC10435754 DOI: 10.3389/fonc.2023.1184841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/26/2023] [Indexed: 08/22/2023] Open
Abstract
Background Oxidative stress plays a significant role in the tumorigenesis and progression of tumors. We aimed to develop a prognostic signature using oxidative stress-related genes (ORGs) to predict clinical outcome and provide light on the immunotherapy responses of clear cell renal cell carcinoma (ccRCC). Methods The information of ccRCC patients were collected from the TCGA and the E-MTAB-1980 datasets. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) were conducted to screen out overall survival (OS)-related genes. Then, an ORGs risk signature was built by multivariate Cox regression analyses. The performance of the risk signature was evaluated with Kaplan-Meier (K-M) survival. The ssGSEA and CIBERSORT algorithms were performed to evaluate immune infiltration status. Finally, immunotherapy responses was analyzed based on expression of several immune checkpoints. Results A prognostic 9-gene signature with ABCB1, AGER, E2F1, FOXM1, HADH, ISG15, KCNMA1, PLG, and TEK. The patients in the high risk group had apparently poor survival (TCGA: p < 0.001; E-MTAB-1980: p < 0.001). The AUC of the signature was 0.81 at 1 year, 0.76 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.8 at 1 year, 0.82 at 3 years, and 0.83 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis proved the stable clinical prognostic value of the signature (TCGA cohort: HR = 1.188, 95% CI =1.142-1.236, p < 0.001; E-MTAB-1980 cohort: HR =1.877, 95% CI= 1.377-2.588, p < 0.001). Clinical features correlation analysis proved that patients in the high risk group were more likely to have a larger range of clinical tumor progression. The ssGSEA and CIBERSORT analysis indicated that immune infiltration status were significantly different between two risk groups. Finally, we found that patients in the high risk group tended to respond more actively to immunotherapy. Conclusion We developed a robust prognostic signature based on ORGs, which may contribute to predict survival and guide personalize immunotherapy of individuals with ccRCC.
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Affiliation(s)
- Xin Wu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Fenghua Li
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Wenjie Xie
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Binbin Gong
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Bin Fu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Weimin Chen
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Libo Zhou
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Lianmin Luo
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
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Yang L, Yu Q, Zhu Y, Ali Mallah M, Wang W, Feng F, Zhang Q. Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis. Int J Environ Health Res 2023; 33:243-257. [PMID: 34961365 DOI: 10.1080/09603123.2021.2016660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 12/05/2021] [Indexed: 06/14/2023]
Abstract
This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.
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Affiliation(s)
- Liu Yang
- Department of Toxicology, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
| | - Qi Yu
- Department of Toxicology, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
| | - Yonghang Zhu
- Department of Toxicology, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
| | - Manthar Ali Mallah
- Department of Toxicology, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
| | - Wei Wang
- Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
| | - Feifei Feng
- Department of Toxicology, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
| | - Qiao Zhang
- Department of Toxicology, College of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou, Henan Province, China
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Kim GH, Heo HJ, Kang JW, Kim EK, Baek SE, Kim K, Kim IJ, Suh S, Lee BJ, Kim YH, Pak K. Multi-omics analysis revealed TEK and AXIN2 are potential biomarkers in multifocal papillary thyroid cancer. Cancer Cell Int 2022; 22:185. [PMID: 35550582 PMCID: PMC9097102 DOI: 10.1186/s12935-022-02606-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 05/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Papillary thyroid carcinoma (PTC), the most common endocrine cancer, accounts for 80-85% of all malignant thyroid tumors. This study focused on identifying targets that affect the multifocality of PTC. In a previous study, we determined 158 mRNAs related to multifocality in BRAF-mutated PTC using The Cancer Genome Atlas. METHODS We used multi-omics data (miRNAs and mRNAs) to identify the regulatory mechanisms of the investigated mRNAs. miRNA inhibitors were used to determine the relationship between mRNAs and miRNAs. We analyzed the target protein levels in patient sera using ELISA and immunohistochemical staining of patients' tissues. RESULTS We identified 44 miRNAs that showed a negative correlation with mRNA expression. Using in vitro experiments, we identified four miRNAs that inhibit TEK and/or AXIN2 among the target mRNAs. We also showed that the downregulation of TEK and AXIN2 decreased the proliferation and migration of BRAF ( +) PTC cells. To evaluate the diagnostic ability of multifocal PTC, we examined serum TEK or AXIN2 in unifocal and multifocal PTC patients using ELISA, and showed that the serum TEK in multifocal PTC patients was higher than that in the unifocal PTC patients. The immunohistochemical study showed higher TEK and AXIN2 expression in multifocal PTC than unifocal PTC. CONCLUSIONS Both TEK and AXIN2 play a potential role in the multifocality of PTC, and serum TEK may be a diagnostic marker for multifocal PTC.
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Affiliation(s)
- Ga Hyun Kim
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Yangsan, Republic of Korea
| | - Hye Jin Heo
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Ji Wan Kang
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Yangsan, Republic of Korea
| | - Eun-Kyung Kim
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Seung Eun Baek
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea
| | - Keunyoung Kim
- Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - In Joo Kim
- Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Sunghwan Suh
- Department of Internal Medicine, Dong-A University College of Medicine, Busan, Republic of Korea
| | - Byung-Joo Lee
- Department of Otorhinolaryngology-Head and Neck Surgery, Pusan National University Hospital, Busan, Republic of Korea
| | - Yun Hak Kim
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, Republic of Korea. .,Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea. .,Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, Republic of Korea.
| | - Kyoungjune Pak
- Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea.
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Wang B, Liu L, Wu J, Mao X, Fang Z, Chen Y, Li W. Construction and Verification of a Combined Hypoxia and Immune Index for Clear Cell Renal Cell Carcinoma. Front Genet 2022; 13:711142. [PMID: 35222525 PMCID: PMC8863964 DOI: 10.3389/fgene.2022.711142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 01/21/2022] [Indexed: 11/13/2022] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive malignancies in humans. Hypoxia-related genes are now recognized as a reflection of poor prognosis in cancer patients with cancer. Meanwhile, immune-related genes play an important role in the occurrence and progression of ccRCC. Nevertheless, reliable prognostic indicators based on hypoxia and immune status have not been well established in ccRCC. The aims of this study were to develop a new gene signature model using bioinformatics and open databases and to validate its prognostic value in ccRCC. The data used for the model structure can be accessed from The Cancer Genome Atlas database. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the hypoxia- and immune-related genes associated with prognostic risk, which were used to develop a characteristic model of prognostic risk. Kaplan-Meier and receiver-operating characteristic curve analyses were performed as well as independent prognostic factor analyses and correlation analyses of clinical characteristics in both the training and validation cohorts. In addition, differences in tumor immune cell infiltrates were compared between the high and low risk groups. Overall, 30 hypoxia- and immune-related genes were identified, and five hypoxia- and immune-related genes (EPO, PLAUR, TEK, TGFA, TGFB1) were ultimately selected. Survival analysis showed that the high-risk score on the hypoxia- and immune-related gene signature was significantly associated with adverse survival outcomes. Furthermore, clinical ccRCC samples from our medical center were used to validate the differential expression of the five genes in tumor tissue compared to normal tissue through quantitative real-time polymerase chain reaction (qRT-PCR). However, more clinical trials are needed to confirm these results, and future experimental studies must verify the potential mechanism behind the predictive value of the hypoxia- and immune-related gene signature.
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Affiliation(s)
- Bin Wang
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lixiao Liu
- Department of Obstetrics and Gynecology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jinting Wu
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaolu Mao
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhen Fang
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yingyu Chen
- Department of Neurosurgery, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Wenfeng Li
- Department of Medical Oncology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
- *Correspondence: Wenfeng Li,
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Mahfuz AMUB, Zubair-Bin-Mahfuj AM, Podder DJ. A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma. Genomics Inform 2021; 19:e16. [PMID: 34261301 PMCID: PMC8261271 DOI: 10.5808/gi.21019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/05/2021] [Accepted: 05/15/2021] [Indexed: 11/20/2022] Open
Abstract
Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.
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Affiliation(s)
- A. M. U. B. Mahfuz
- Department of Biotechnology & Genetic Engineering, Faculty of Life Science, University of Development Alternative, Dhaka 1209, Bangladesh
| | | | - Dibya Joti Podder
- Department of General Surgery, Sher-E-Bangla Medical College, Barishal 8200, Bangladesh
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Huang Z, Wang S, Zhang HJ, Zhou YL, Tang X, Shi JH. Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature. Transl Lung Cancer Res 2021; 10:2132-2147. [PMID: 34164265 PMCID: PMC8182713 DOI: 10.21037/tlcr-20-1314] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background The mechanisms of hypoxia or immune microenvironment in cancer have been studied respectively, but the role of hypoxia immune microenvironment in non-small cell lung cancer (NSCLC) still needs further exploration. Methods By applying the K-means algorithm, 1,121 patients with NSCLC were divided into three categories. We evaluated the constructed signature in order to link it with the prognosis, which was constructed by univariate and least absolute shrinkage operator (LASSO) Cox regression analysis. Results A total of three clusters were obtained by clustering five Gene Expression Omnibus (GEO) data sets. Gene Set Variation Analysis (GSVA) and immune infiltration analysis were performed to explore the biological behavior. Cluster one presented an activated state of oncogenic pathways, and compared with the other two clusters, the median risk score was the highest, which was the reason for its poor survival. Cluster three showed that the immune pathway was active and the median risk score was the lowest, so the survival was the best. However, cluster two presented a state in which both immune and matrix pathways were activate. This was manifested as mutual antagonism, and its risk score was in the middle. Its survival was in the middle. Conclusions This work revealed the role of hypoxia related genes (HRGs) modification in tumor microenvironment, which was conducive to our comprehensive analysis of the prognosis of NSCLC, and provided direction and guidance for clinical immunotherapy.
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Affiliation(s)
- Zhanghao Huang
- Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Nantong, China.,Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China.,Medical College of Nantong University, Nantong, China
| | - Shuo Wang
- Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Nantong, China.,Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China.,Medical College of Nantong University, Nantong, China
| | - Hai-Jian Zhang
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China
| | - You Lang Zhou
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China
| | - Xin Tang
- Key Laboratory of Neuroregeneration of Jiangsu and Ministry of Education, Co-Innovation Center of Neuroregeneration, Nantong University, Nantong, China
| | - Jia-Hai Shi
- Nantong Key Laboratory of Translational Medicine in Cardiothoracic Diseases, and Research Institution of Translational Medicine in Cardiothoracic Diseases, Affiliated Hospital of Nantong University, Nantong, China.,Department of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China
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Liao Z, Yao H, Wei J, Feng Z, Chen W, Luo J, Chen X. Development and validation of the prognostic value of the immune-related genes in clear cell renal cell carcinoma. Transl Androl Urol 2021; 10:1607-1619. [PMID: 33968649 PMCID: PMC8100830 DOI: 10.21037/tau-20-1348] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Background Clear cell renal cell carcinoma (ccRCC) is a highly heterogeneous tumor, resulting a challenge of developing target therapeutics. Not long ago, immune checkpoint blockade regimens combine with tyrosin kinase inhibitors have evolved frontline options in metastatic RCC, which implies arrival of the era of tumor immunotherapy. Studies have demonstrated immune-related genes (IRGs) could characterize tumor milieu and related to patient survival. Nevertheless, the clinical significance of classifier depending on IRGs in ccRCC has not been well established. Methods The R package limma, univariate and LASSO cox regression analysis were used to screen the prognostic related IRGs from TCGA database. Multivariate cox regression was utilized to establish a risk prediction model for candidate genes. Quantitative real-time PCR was used to confirm the expression of candidates in clinical samples from our institution. CIBERSORT algorithm and correlation analysis were applied to explore tumor-infiltrating immune cells signature between different risk groups. A clinical nomogram was also developed to predict OS by using the rms R package based on the risk prediction model and other independent risk factors. The ICGC data was used for external validation of either gene risk model or nomogram. Results We identified 382 differentially expressed immune related genes. Four unique prognostic IRGs (CRABP2, LTB4R, PTGER1 and TEK) were finally affirmed to associate with tumor survival independently and utilized to establish the risk score model. All candidates’ expression was successfully laboratory confirmed by q-PCR. CIBERSORT analysis implied patients in unfavorable-risk group with high CD8 T cell, regulatory T cell and NK cell infiltration, as well as high expression of PD-1, CTLA4, TNFRSF9, TIGIT and LAG3. A nomogram combined IRGs risk score with age, gender, TNM stage, Fuhrman grade, necrosis was further generated to predict of 3- and 5-year OS, which exhibited superior discriminative power (AUCs were 0.811 and 0.795). Conclusions Our study established and validated a survival prognostic model system based on 4 unique immune related genes in ccRCC, which expands knowledge in tumor immune status and provide a potent prediction tool in future.
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Affiliation(s)
- Zhuangyao Liao
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Haohua Yao
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Jinhuan Wei
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zihao Feng
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wei Chen
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Junhang Luo
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xu Chen
- Department of Urology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Chen S, Yu M, Ju L, Wang G, Qian K, Xiao Y, Wang X. The immune-related biomarker TEK inhibits the development of clear cell renal cell carcinoma (ccRCC) by regulating AKT phosphorylation. Cancer Cell Int 2021; 21:119. [PMID: 33602230 DOI: 10.1186/s12935-021-01830-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 02/10/2021] [Indexed: 12/19/2022] Open
Abstract
Background High immunogenicity is an important feature of ccRCC, but its underlying immune-related molecular mechanisms remain unclear. This study aimed to investigate the effect of immune-related gene TEK on ccRCC and its prognostic value. Methods The immune-related differentially expressed genes (DEGs) and transcription factors (TFs) in ccRCC were screened based on The Cancer Genome Atlas (TCGA) database, and a regulatory network of TF was constructed. Prognostic-related immune genes were screened by univariate Cox regression analysis and functional annotation was performed. Univariate and multivariate Cox regression analyses were performed to construct the immune gene risk model and identify the hub gene TEK that independently affected the prognosis of ccRCC. The effectiveness of the TEK was verified by external microarray datasets. The relationship between TEK and immune cells in ccRCC was evaluated based on Tumor Immune Estimation Resource (TIMER). The expression of TEK in clinical specimens was verified by qRT-PCR and immunohistochemical (IHC) staining. MTT and cloning formation assay were used to evaluate cell proliferation. Transwell assays were used to assess cell migration. Apoptosis was assessed by flow cytometry, and the expression of related proteins was detected by Western blot and immunofluorescence. Results We constructed a prognostic model consisting of 12 hub genes and performed risk scores to determine the relationship between these scores and prognosis. Through Cox regression analysis and survival analysis, TEK, an immune marker highly related to survival prognosis, was obtained and validated. In vitro experiments showed that knockdown of TEK promoted the proliferation and migration of ccRCC cells, and we found that TEK promoted apoptosis by regulating the phosphorylation of AKT, thereby inhibiting cell proliferation. Conclusions TEK plays an important role in risk assessment and survival prediction for ccRCC patients as a new immune gene and maybe an emerging target for immunotherapy for ccRCC patients.
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Ye GC, Liu YF, Huang L, Zhang CY, Sheng YL, Wu B, Han L, Wu CL, Dong B, Qi Y. Key microRNAs and hub genes associated with poor prognosis in lung adenocarcinoma. Aging (Albany NY) 2021; 13:3742-62. [PMID: 33461176 DOI: 10.18632/aging.202337] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 10/08/2020] [Indexed: 12/12/2022]
Abstract
In the study, we obtained 36 pairs of lung adenocarcinoma (LUAD) tissues and adjacent non-tumorous tissues. Then, we chose a specific hub-target gene of miRNA and used qRT-PCR to evaluate the expression of PECAM1. We found that the expression level of PECAM1 mRNA in LUAD was significantly lower than that in adjacent nontumor tissues (P<0.0001). Univariate and multivariate analyses were conducted on 481 LUAD patients from The Cancer Genome Atlas (TCGA) according to the Cox proportional hazard regression model to evaluate the impact of PECAM1 expression and other clinicopathological factors on survival. The results showed that the low expression of PECAM1 was an important independent predictor of poor overall survival (HR, 0.704; 95% CI, 0.518-0.957; P = 0.025). Based on the Tumor Immune Estimation Resource (TIMER) database, the relationship between PECAM1 expression and B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD (P<0.01). In particular, a more significant positive correlation between PECAM1 expression and HLA-complex members, CD1C, NRP1, and ITGAX expression in dendritic cell was detected in LUAD. The mechanism which PECAM1 involved in the development of LUAD may be closely related to changes in the immune microenvironment.
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He Z, Deng T, Duan X, Zeng G. Profiles of overall survival-related gene expression-based risk signature and their prognostic implications in clear cell renal cell carcinoma. Biosci Rep 2020; 40:BSR20200492. [PMID: 32789468 DOI: 10.1042/BSR20200492] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 08/05/2020] [Accepted: 08/06/2020] [Indexed: 12/17/2022] Open
Abstract
The present work aimed to evaluate the prognostic value of overall survival (OS)-related genes in clear cell renal cell carcinoma (ccRCC) and to develop a nomogram for clinical use. Transcriptome data from The Cancer Genome Atlas (TCGA) were collected to screen differentially expressed genes (DEGs) between ccRCC patients with OS > 5 years (149 patients) and those with <1 year (52 patients). In TCGA training set (265 patients), seven DEGs (cytochrome P450 family 3 subfamily A member 7 (CYP3A7), contactin-associated protein family member 5 (CNTNAP5), adenylate cyclase 2 (ADCY2), TOX high mobility group box family member 3 (TOX3), plasminogen (PLG), enamelin (ENAM), and collagen type VII α 1 chain (COL7A1)) were further selected to build a prognostic risk signature by the least absolute shrinkage and selection operator (LASSO) Cox regression model. Survival analysis confirmed that the OS in the high-risk group was dramatically shorter than their low-risk counterparts. Next, univariate and multivariate Cox regression revealed the seven genes-based risk score, age, and Tumor, lymph Node, and Metastasis staging system (TNM) stage were independent prognostic factors to OS, based on which a novel nomogram was constructed and validated in both TCGA validation set (265 patients) and the International Cancer Genome Consortium cohort (ICGC, 84 patients). A decent predictive performance of the nomogram was observed, the C-indices and corresponding 95% confidence intervals of TCGA training set, validation set, and ICGC cohort were 0.78 (0.74–0.82), 0.75 (0.70–0.80), and 0.70 (0.60–0.80), respectively. Moreover, the calibration plots of 3- and 5 years survival probability indicated favorable curve-fitting performance in the above three groups. In conclusion, the proposed seven genes signature-based nomogram is a promising and robust tool for predicting the OS of ccRCC, which may help tailor individualized therapeutic strategies.
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Berglund A, Amankwah EK, Kim YC, Spiess PE, Sexton WJ, Manley B, Park HY, Wang L, Chahoud J, Chakrabarti R, Yeo CD, Luu HN, Pietro GD, Parker A, Park JY. Influence of gene expression on survival of clear cell renal cell carcinoma. Cancer Med 2020; 9:8662-8675. [PMID: 32986937 PMCID: PMC7666730 DOI: 10.1002/cam4.3475] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 09/03/2020] [Accepted: 09/05/2020] [Indexed: 12/14/2022] Open
Abstract
Approximately 10%‐20% of patients with clinically localized clear cell renal cell carcinoma (ccRCC) at time of surgery will subsequently experience metastatic progression. Although considerable progression was seen in the systemic treatment of metastatic ccRCC in last 20 years, once ccRCC spreads beyond the confines of the kidney, 5‐year survival is less than 10%. Therefore, significant clinical advances are urgently needed to improve overall survival and patient care to manage the growing number of patients with localized ccRCC. We comprehensively evaluated expression of 388 candidate genes related with survival of ccRCC by using TCGA RNAseq (n = 515), Total Cancer Care (TCC) expression array data (n = 298), and a well characterized Moffitt RCC cohort (n = 248). We initially evaluated all 388 genes for association with overall survival using TCGA and TCC data. Eighty‐one genes were selected for further analysis and tested on Moffitt RCC cohort using NanoString expression analysis. Expression of nine genes (AURKA, AURKB, BIRC5, CCNE1, MK167, MMP9, PLOD2, SAA1, and TOP2A) was validated as being associated with poor survival. Survival prognostic models showed that expression of the nine genes and clinical factors predicted the survival in ccRCC patients with AUC value: 0.776, 0.821 and 0.873 for TCGA, TCC and Moffitt data set, respectively. Some of these genes have not been previously implicated in ccRCC survival and thus potentially offer insight into novel therapeutic targets. Future studies are warranted to validate these identified genes, determine their biological mechanisms and evaluate their therapeutic potential in preclinical studies.
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Affiliation(s)
- Anders Berglund
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Ernest K Amankwah
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Cancer and Blood Disorders Institute, Johns Hopkins All Children's Hospital, Saint Petersburg, FL, USA
| | - Young-Chul Kim
- Department of Biostatistics, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Philippe E Spiess
- Department of Genitourinary Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Wade J Sexton
- Department of Genitourinary Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Brandon Manley
- Department of Genitourinary Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA.,Department of Integrated Mathematical Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Hyun Y Park
- Department of Cancer Epidemiology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Liang Wang
- Department of Tumor Biology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Jad Chahoud
- Department of Genitourinary Oncology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Ratna Chakrabarti
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL, USA
| | - Chang D Yeo
- Division of Pulmonology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Hung N Luu
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.,Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Giuliano D Pietro
- Department of Pharmacy, Universidade Federal de Sergipe, Sao Cristovao, Brazil
| | - Alexander Parker
- University of Florida College of Medicine, Jacksonville, FL, USA
| | - Jong Y Park
- Department of Cancer Epidemiology, Moffitt Cancer Center and Research Institute, Tampa, FL, USA
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Hu D, Zhou M, Zhu X. Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer. Biomed Res Int 2019; 2019:2506843. [PMID: 31886185 DOI: 10.1155/2019/2506843] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 10/11/2019] [Accepted: 10/17/2019] [Indexed: 12/27/2022]
Abstract
Background To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. Methods We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1, P value <0.05 by using package "limma" in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan-Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. Results A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. Conclusions Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.
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